Preliminary Investigation of the Panic Screening Score for Emergency Department Patients With Unexplained Chest Pain
Bibliographic record
Abstract
OBJECTIVES: The objective was to demonstrate the derivation and the preliminary validation of a brief screening score to improve recognition of panic-like anxiety in emergency department (ED) patients with unexplained chest pain. METHODS: This cross-sectional study included 507 ED patients with unexplained chest pain randomly assigned to the derivation condition (n = 201) or the validation condition (n = 306). The Anxiety Disorders Interview Schedule for DSM-IV (ADIS-IV) acted as the criterion standard for panic diagnosis. Receiver operating characteristic (ROC) curves were used to determine which of the sociodemographic, medical, and questionnaire response variables best predicted the presence of panic-like anxiety in the derivation condition. The selected predictors were entered in a logistic regression analysis to determine variables to be included in the screening score. The predictive validity of the resulting score was evaluated in both conditions. RESULTS: The four-item Panic Screening Score (PSS) identified panic-like anxiety with a sensitivity of 63% (95% confidence interval [CI] = 52% to 73%) and a specificity of 84% (95% CI = 76% to 90%) in the derivation phase. The positive predictive value was 74% (95% CI = 62% to 93%) and the negative predictive value was 76% (95% CI = 68% to 89%). In the validation phase, the sensitivity and specificity were 53% (95% CI = 44% to 62%) and 85% (95% CI = 78% to 89%), respectively. The positive predictive value was 72% (95% CI = 62% to 80%) and the negative predictive value was 71% (95% CI = 65% to 77%). CONCLUSIONS: The PSS may be useful to identify patients with unexplained chest pain who could benefit from referral to mental health professionals or their primary care providers for evaluation of panic attack and panic disorder. Prospective studies to improve and validate the PSS, followed by impact analysis, are mandatory before clinical implementation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".